Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Loic Coyle"'
Publikováno v:
Frontiers in Physics, Vol 10 (2023)
In the Large Hadron Collider, the beam losses are continuously measured for machine protection. By design, most of the particle losses occur in the collimation system, where the particles with high oscilla-tion amplitudes or large momentum error are
Externí odkaz:
https://doaj.org/article/9c528cb1a17d4f8a84c39cbef9bf32ec
Autor:
Stefano Redaelli, Benoit Salvant, F. Blanc, Roberto Prevete, Matteo Solfaroli Camillocci, Jorg Wenninger, F. Giordano, Massimo Giovannozzi, Tatiana Pieloni, Elena Fol, Loic Coyle, Gabriella Azzopardi, Xavier Buffat, Pasquale Arpaia, Rogelio Tomás, Gianluca Valentino, Michael Schenk, Frederik Van Der Veken, Belen Salvachua
Particle accelerators are among the most complex instruments conceived by physicists for the exploration of the fundamental laws of nature. Of relevance for particle physics are the high-energy colliders, such as the CERN Large Hadron Collider (LHC),
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::024bf8116196a46fab9d5ecaacadd7a1
http://cds.cern.ch/record/2777343
http://cds.cern.ch/record/2777343
Autor:
Massimo Giovannozzi, Stefano Redaelli, Loic Coyle, Tatiana Pieloni, Rogelio Tomas Garcia, Gabriella Azzopardi, Belen Salvachua, Michael Schenk, Leonid Rivkin, Frederik Van Der Veken, Gianluca Valentino, Elena Fol, F. Blanc
Publikováno v:
Proceedings of European Physical Society Conference on High Energy Physics — PoS(EPS-HEP2019).
Machine learning techniques have been used extensively in several domains of Science and Engineering for decades. These powerful tools have been applied also to the domain of high-energy physics, in the analysis of the data from particle collisions,
Autor:
Rogelio Tomas Garcia, Tatiana Pieloni, Gianluca Valentino, Frederik Van Der Veken, Gabriella Azzopardi, F. Blanc, Elena Fol, Michael Schenk, Massimo Giovannozzi, Loic Coyle, Belen Maria Salvachua Ferrando, Stefano Redaelli
With the advent of Machine Learning a few decades ago, Science and Engineering have had new powerful tools at their disposal. Particularly in the domain of particle physics, Machine Learning techniques have become an essential part in the analysis of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a92dc158f93393129c3e6f556cdb3f9
http://cds.cern.ch/record/2799883
http://cds.cern.ch/record/2799883